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KP Unpacked
KP Unpacked explores the biggest ideas in AEC, AI, and innovation, unpacking the trends, technology, discussions, and strategies shaping the built environment and beyond.
KP Unpacked
Construction Is the Last Automation Frontier
This is our final episode of the year, and we’re ending it with the kind of conversation AEC needs more of.
In this episode of KP Unpacked, KP sits down with Dr. Barry Clark (CTO) to connect the dots from “physical startups” (robots sewing denim) to what comes next: robots + humans coexisting on jobsites, AI-driven motion control, and a coming wave of materials + manufacturing innovation that could reshape how we design and build.
If you’re a founder, operator, or AEC leader wondering what’s real vs. vaporware, this one will sharpen your lens.
If you truly meant “last podcast of 2035,” just swap the year, but “final episode of the year” keeps it accurate either way.
Key topics covered
- From robotics in apparel to robotics in construction: why “physical startups” are back
- Why construction is the hardest automation environment (unstructured, bespoke, constant pivots)
- AI’s impact on robotics: from brittle logic to learning systems that handle “unknown unknowns”
- Digital twins + simulation: getting cheaper, more practical, closer to daily use
- KP’s thesis: a materials renaissance for AEC—and the real bottleneck (commercial scale)
- What “motion control” actually means (path planning + actuator control)
- The missing layer: orchestration across people + robots on live jobsites
- A hard truth: project tools often become archives, not systems that drive behavior
Guest bio
Dr. Barry Clark is KPR’s CTO with a background in mechanical engineering, optimal control, computer vision, and automation, spanning robotics startups and large-scale automated assembly (including server assembly and software-defined manufacturing).
Turn your 2026 plan into real Q1 momentum.
Join KP Reddy and a small room of AEC leaders on January 13 in the SF Bay Area for the first KPR Quarterly, where strategy meets execution in the first 90 days.
👉 Learn more: https://kpreddy.co/kpr-quarterlies?utm_source=buzzsprout&utm_medium=organic-social&utm_campaign=lead-gen-boost
Hey everybody, this is KB Ready and we are doing something a little different for um Nick Durham. Funny story. I thought Nick was in New York because he was, but um, like I said, we don't communicate that well sometimes about the podcast because it's kind of like an extracurricular. And so funny story is uh asked Barry Barry Clark, Dr. Barry Clark, our CTO, to join me since Nick was not joining us. And when we were in the backstage room, Nick showed up. So we had to make a decision like uh so we booted Nick. Y'all hear enough of uh me and Nick. So uh but today we're joined with Dr. Barry Clark, our CTO, and um thought we'd have a more interesting conversation than me and Nick talking about nicotine pack nicotine pouches and uh all the other random things that we sometimes talk about. So welcome, Barry.
SPEAKER_02:Thanks, KP. Happy to be here.
SPEAKER_00:So um we knew we we've known each other back when it was kind of funny. I sent you a picture of my of my two older boys at the open house at software, where I had my middle kid on my shoulders. He is now 22 years old, and um probably I can probably get on his shoulders. He's probably not getting on my shoulders. I don't think I can carry him. So what year was that at Software?
SPEAKER_02:Is that uh I think it was 14 or 15, uh 2014, 2015, because my vivid memory is um somewhere right around then we were all in on a Sunday, and you brought them in to help us uh cut denim uh for our automated sewing process. Yeah. So that was one of my more vivid memories.
SPEAKER_00:Yeah, because it was funny. So we're uh for context, we were uh both uh at a company called Software Automation. We're building robots to sew clothes, so you know, replace the tedious tasks of uh manual seamstresses, you know, tearing up their fingers and all, which it's still fairly manual. Um so we were innovating that and we spun out of Georgia Tech and started a company. And um, so we had robots that could sew genes, um, but we did not buy the cutting systems. So run away. Yeah, yeah. The statute of limitations on child labor, I think it's like five years. I think we're okay. I think we're okay. But but that was that was a fun time because one, um, you know, physical startups are now much, you know. We saw the announcement from Boom doing gas turbine, so physical startups are back, right? And our friends at General Catalyst are doing all these physical startups, you know, the androuls of the world and all that. But back then, when we were doing a quote unquote physical startup, it was the height of SaaS startups, and people were like, Well, I mean, that's insane. Like, how can you even do that?
SPEAKER_02:Um, so it was it was definitely a different time, and yeah, you think about 3D printing, right? Was relatively novel at the time, right? Like the fact that we had three Prusses running 24-7 in the corner, and now that's you know, a lot of hobbyists do the same thing, right?
SPEAKER_00:So um, yeah, it was yeah, I I live in Half Moon Bay, and our local library has a 3D printer. Yeah, you can go and they have a little maker space, you can go print stuff. It stays pretty busy apparently. But but I was like, it was I mean, we act like that was so long ago, that was 10 years, right? That was 10 years, and it was hard. It was hard.
SPEAKER_02:Yeah, it was very hard. I mean, I think um if you look at the evolution of manufacturing shops, right, how much easier it is to get things made today, uh, sensors, right? If you look at how much we were paying for cameras uh to drive our computer vision systems versus the quality that you can get off of Amazon or Alibaba today, um the idea of having 3D scanners, right, commercially available. That was something that was nearly impossible to get high quality at the time off the shelf. Um, so yeah, we've come a long way. Uh I think we were maybe we were a little ahead of our time. Uh, but yeah, it was it was a fun time for sure.
SPEAKER_00:And um, just for everyone's sake, just a little background kind of educationally, um, what you worked on in terms of your thesis and all that stuff. And then when you talk about like your last gig at Bright Machines, which was also hardware.
SPEAKER_02:Yeah, of course. Um, so my background is in mechanical engineering. Um, when I was undergrad, I was for one semester uh computer science plus mechanical, decided I wanted to make sure I finished in four years. Uh so stuck with mechanical, which was my first love. Studied control theory uh in grad school with a focus on optimal control uh and legged robots. Um, and then yeah, out of grad school, I joined software automation where we met. Um, and that's where I picked up kind of my love for computer vision like how do you incorporate that into control systems? Um, and then that led me more into software development, um, developing software kind of at the intersection of the physical world. And that's really where my passion lies. And for the last six years, working for Bright Machines focused on automated assembly, uh, a lot of which centered around electronics in a box. And we sort of worked our way around different market segments. And a couple of years ago, we settled on server assembly, and that was our focus on doing software-defined manufacturing in that space. How can you use flexible robotics driven by computer vision and force sensing to um have really complex automation tasks done on different products in a in a very flexible and fast manner?
SPEAKER_00:Cool. And I um, you know, on my LinkedIn on my LinkedIn profile, it says AI design buildings, robots build buildings. That's all it says. And so I put that on there, and then and and then you came on board to not make me a liar, uh, which I always say that like uh my my job is to uh for Barry not to make me a liar and for me not to make him a liar. There's a lot of lying going on in technology for those of you that don't know. There's a lot of vaporware, there's a lot of hype, there's a lot of stuff. So Barry and I do this thing where it's like, is that reasonable, realistic, probabilistic, or is it just like pie in the sky? But I mean, when we think about like in and we've stayed in touch, obviously, um, all those years. Um, and I always say, like, it's so hard to attract talent to the construction world, the engineering world, because it's kind of in in many ways, it's boring. But uh, besides my good looks and charisma, you you joined us, or maybe it's in spite of. Um, I mean, what do you see interesting in this in like the built world?
SPEAKER_02:I mean, you know, I am a hands-on kind of person, right? So uh in some ways, my answer might be different than what it would be for your average software engineer. Um, when we purchased a house, I became obsessed with construction, right? Being able to touch things, seeing things manifest themselves in a physical way, using natural products, right, state-of-the-art products. Um, to me, that is really, really interesting, right? Um, but then knowing that uh the industry struggles, right, to stay on budget, to stay on time, to deliver things uh in novel ways, right? Um so in the same way that 10 years ago, right, automated assembly seemed like the last frontier of automation. Uh, I think I, you know, that's not correct, right? I think it's really construction. And that's a that's really what um attracts me to the industry. I think what can attract other people is that for so long, construction seemed out of reach, right? The fact that the environment is so unstructured, right? Uh that every day is different, right? Different people show up, different things are happening. At the last minute, you may need to pivot what you're doing that day because what may or may not have arrived on site. Um, and with the evolution of different algorithms, AI sensing, right, bringing the cost of hardware down, I think we're finally at a point where you can really start to apply some of these technologies into this very complicated, unstructured environment.
SPEAKER_00:Yeah. That was that was part of our hypothesis that software was automation and robotics finally got computer vision. You didn't have to have these really expensive, you know, that it had gotten more cost efficient that you could use like automated systems in the apparel industry. Um, but even since then, it's just like it's a whole nother world now in terms of costs and and and the ability to to build this stuff, you know, it's just not as big of a lift as it was even five years ago.
SPEAKER_02:Oh, totally. I mean, I think you know, Spark Fun was just beginning to like pick up a lot of traction when we were working together. Um, but it was still sort of hobby type equipment, right? Um, the equipment that you put your hands on today that might be considered hobby is really not that far from industrial grade in a lot of cases, right? And so I think that really does make a difference in terms of how quickly you can get things to market, how much they cost. Um yeah, it's it's a really fascinating time.
SPEAKER_00:And um, you know, you said like, well, hey, it looks like time is the time is now to be able to innovate in the construction industry. Um, and and you've already, you know, you've been been working on this stuff for the last three, four months. So you've already seen some insights. So how how do you think like the differences in terms of construction and how you think about like where you came from in terms of more industrialized manufacturing?
SPEAKER_02:Um, I mean, one of the main things that comes to mind is at least, you know, in the US, right? Um, everything is bespoke, right? Everything is a one-off. Even, you know, for the things that we were type, you know, that we were thinking about and trying to do with software automation, where we were thinking about small batch manufacturing, right? Um, doing custom sizes for each individual, even then, you know, those those jeans, right, or that t-shirt um still look the same, right? Even if the dimensions were slightly different. That's typically not the case with houses, right? Uh, or you know, hotels or hospitals. They're all very different. And there's there's been a lot of interesting innovation in terms of trying to standardize certain parts, manufacturing, you know, sections of things within factories. Um, but at the end of the day, they're still all very bespoke, right? The geography where you're doing the construction is different. Uh, so this unstructured part of the problem, I think, is what's really interesting and what distinguishes it uh from the you know manufacturing plant. Um, and really where, you know, hopefully we'll be able to innovate uh in the near future because of all the disruption that's taking place.
SPEAKER_00:Yeah. And you, I mean, I think we if you look at the AI narrative and how heavy it's biased towards software, and I think you we we talk, you know, a couple times a day. So um, and I think we continue to be impressed with AI's impact on being able to write more code and and do the things, accelerating those. And and I think that people talk about that a lot, right? Um but when you think about like hardware and how that's how do you think about AI and kind of robotics and how what impact it's having kind of on the robotics space?
SPEAKER_02:Um yeah, I I mean I think that's a good question. I think you know, if you look at uh a long time ago, if you look at how um Boston Dynamics was doing in their walking robots, right? It was thousands and thousands of lines of basically if statements.
SPEAKER_01:Yeah.
SPEAKER_02:Um there was, you know, my favorite quote, which I you know beat to death is basically the unknown unknowns of robotics, right? Which 10 or 15 years ago, you spend you know five to nine years getting your PhD, and you can make that robot walk, and you have no idea how you did it, right? Because you write this paper, these beautiful equations, and you end up just tuning these magic numbers, right? Or tweaking the hardware to kind of make it work. Um, all of that gets embedded, you know, in AI now, right? Uh in these neural networks, the that understanding, the ability to kind of model what doesn't exactly follow the physical equations think of. Um, and so I I really think it makes it easier. You can take less expensive hardware, right? Hardware that has flaws. You don't have to focus uh as closely on you know your physical models, right? Uh, because as you train, you're naturally gonna kind of get some of those dynamics built into the model, right? So you don't have to be as smart, right? So I think that's one way in which it helps. Um, generative design has been around for a long time, right? But actually applying AI to improve the hardware, right? Like how can we make better hardware from these options, taking this information we we already have and uh optimizing, right, for the situations that we're we're putting things in. Um, I think you know, digital twins have been around for a really long time, um, but I think it's always been hard to justify the use case, but they're getting easier and easier to use, they're getting cheaper and cheaper to run. So at some point, the ability to simulate your hardware before you build it uh with high fidelity is going to be real, right? There's great examples of people doing that today. Now they still I I still tend to believe the amount of effort they put in is pretty high to get it to work. So the hardware you're building has to be worth it, right? But at some point you'll be able to simulate relatively simple designs, right? Um, in a cost-effective manner before you before you actually build them.
SPEAKER_00:Yeah. No, it's it's also interesting. I I've been talking to a lot of people about like what is the next uh the next venture fund look like. You know, I'm just a big believer that if um VC has changed a lot, right? So whatever you did last time is probably not what you're gonna do next time. It's just you have to evolve. You can't just say, I'm gonna do what I did in my last fund. But one of the things I've been really studying is thinking about like there's a there's strong narrative around AI and what it's doing, the biotech and life sciences, how drug discovery and different things. I was out with uh on vacation with a bunch of doctors the other day, and one of them used to be the chief medical officer for uh Glaxo, Smith Klein, or whatever. And and you know, and there is this acceleration happening in the in the drug discovery and commercialization space. My general hypothesis is that for our industry, we're gonna see a renaissance of new materials, right? In other words, concrete's been concrete for a long time. Steel is, you know, like there hasn't been a ton of innovation there. But I do think there's gonna be a cycle of material science innovation. And you know, it's not just the innovation, right? If you you you spent time in in the academic research world, I'm sure there's a bunch of stuff on benches of new materials and stronger, lighter, all the things, but getting them into a commercial phase is usually the the big valley of death, both from a funding and a technology. But I, you know, how do you think about like material science and this hypothesis I have that AI could be just like we're thinking about drug discovery uh and highly specialized drugs, right? Personalized medicine. How do you think about how that works in like material science in the future of material science?
SPEAKER_02:Yeah, that's a good question. Um I mean, I think the unknown for me, right, is really around are you driving five percent improvement, right? Or are you driving 500% improvement? And I think that'll be really interesting to see, right? Uh it's not not something that I I have a good feel for. Um, you know, again, I think simulation will play a big part in that. Um and I, you know, um when I was in graduate school, I think I've told you this story before, but uh our design teacher kind of brought out um the rotor from a uh Vietnam helicopter, right? Which was designed purely by hand, right? No FEA, no CAD. Um, and it was you know within like five or 10% of being optimal, right? Because they use the back of the book, right? A thing that we always avoided as mechanical engineering students. Um, and so it will be really interesting to see if the types of materials, the types of synthetics that are out there today are within 10%, right? Um, or if we're actually able to make orders of magnitude improvements, right, by combining things, right, by searching databases that um, you know, people just had a lot of trouble doing, right? Um I guess I would I I would ask you, I mean, is there what what's the last big breakthrough in material science that you think made like a real difference in the construction industry?
SPEAKER_00:I mean, nothing. Like we're we're you know, mass timber, which is just wood, but uh, you know, laminated systems. Um, I mean, you see a lot of innovation on the building product side, right? Like HVAC systems and heat pumps and things like that, which aren't really materials, it's more kind of engineering type stuff. But I think you know, if if you look at part of commercialization of any product and construction, um, is it's just scale, right? Being able to produce enough. I I've seen so many concrete startups that say, Oh, we can take you know, industrial slag and drop it into concrete and it'll make it stronger, whatever. And then when I was like, well, how much of this recycled material can you produce? They're like, Oh, we can produce like a ton a day. And then you talk to the concrete people like that's like an hour at one of our plants, you know. So, so the feedstock, so to speak, to do anything at you know, and in construction at scale, like you know, we've seen some um carbon fiber rebar, glass fiber rebar stuff, but you know, it's such a big industry, if you can't get scale, um, you know, it's very hard. But you know, it's interesting when I talk to structural engineering friends of mine about like AI and what's it gonna do their world, because look, if if you look at structural engineering, like a building, the constraints, right? The variables and constraints are fairly well known. And the sizes of steel, concrete, whatever, they're literally in books, right? They're like it's not we're not inventing new new sizes. Um, so that's very AIable. It's it's a pretty simple problem for AI, right? But and so they're like, well, what are we gonna do with the rest of our time? You know, and I'm like, how about we start thinking about new materials and the commercialization of new materials, uh, and how we can maybe leverage different materials and into buildings. You know, I've seen a bunch of stuff with graphene, right? Like, oh, you can use graphene and structures, and it's like, yeah, but you can't generate enough. So I think to my point is like drug discovery, same thing with material discovery. We can find all kinds of things, but if you can't scale them, the commercialization is always the the really tough one. So in my optimistic world, I think AI is gonna help with that. But then you start thinking too, with just like 3D printing, do I have to build like a composite? At scale, or can I build a custom composite for a specific building to solve a bit specific problem? That might be pretty cool too.
SPEAKER_02:Yeah, that's very interesting. So if you have a construction project that has specific constraints, right, that's a high value project. Can you actually create materials kind of in a batch for that specific project?
SPEAKER_01:Right.
SPEAKER_02:And you could also say that, you know, some of these maybe we're not actually solving for new materials, but AI is helping us figure out how to scale.
SPEAKER_01:Right.
SPEAKER_02:Right. Is also right. So like thinking about what variable are we actually improving, right? Is it the material itself or like how we apply the material? Like uh it's very interesting. Yeah.
SPEAKER_00:Yeah. And it's funny, like um, you know, for all of our architecture listeners that know I kind of give you all a hard time, like it's like the idea that architects design buildings that can't be built, right? It's like it's not reasonable. Well, maybe we do have this unlock that says we can build it, right? We can design things a certain way. I mean, we can't defy gravity, obviously, but sometimes they're thinking about the visual design versus what I, you know, it's like they look at you like, well, why is that beam so big? It's like, well, the beam has to be big, like to tell structural engineering works, right? Like, well, I don't like the way it looks. It's like, well, how important is that, right? How important? Because maybe we can do some, you know, uh some some new material, and that beam's gonna cost you some money, but you know, maybe I can achieve your design, you know, the design aspect of what you're trying to do uh with some new material. So I so I I I think you know, in the worlds of things that I think about, right? These these are the kind of things that I'm constantly like, what's the next the next next thing, right? Yeah, I mean so uh so we haven't seen a ton of robotics and construction. We see pieces and parts, and um and I think it's gonna improve, right? I think it's gonna continually improve. But how do you think, you know, we one of the things we talk about is like great is to design a building, use AI to design a building, check, like whatever. We'll get there, check, right? However, for the second part of my vision of like robots built buildings, we have to convert design into kind of motion control for some robot robots series of robots, right? Which is a whole nother fun technical thing we get to work on. So how how do you I mean, and by the way, just if you can explain to people what motion control is, because we just throw this stuff around.
SPEAKER_02:Yeah, of course. I mean, so motion control can be broken down in my mind into kind of two parts, right? Uh there's what is typically called path planning, right? Which is basically how do I get from point A to point B, right? Or um more at a macro level, where I want my robot to go or what I want it to do. And then there's the kind of micro level or the lower level of how do I then make the robot do that, right? So that usually boils down to uh controlling the actuators, right? Which may be pneumatic, uh, they may be you know gas, like if I'm a uh Waymo car, right? Like exactly how much acceleration am I or how much am I pushing in the pedal effectively? Or maybe how much current I'm like sending to an electric motor, right? So those are those are the two ways that we think about motion control. Um and then I would say, you know, for what we're talking about here, I think what's really interesting, you know, we we talk about in like the software part of AEC, how there's all these point solutions out there, right? Um, how people are tackling difficult problems, but which they may have trouble kind of scaling, right? Um just because of the kind of the niche, right? Like how does it fit in with all these manual processes, right? Yeah. Um, I kind of think about robotics the same way, right? You see some very interesting point solutions for putting up drywall, right? Or doing painting or uh, you know, laying out um sites, but how do you orchestrate all of those together? Right. Like how do you actually kind of map those things together so there is the higher level kind of thinking to start to begin to tell these robots where to go, right? Um and I I think it would be interesting. Can you have an orchestration system that works with humans and robots? Right. Is that like an intermediate step to actually be able to prove out the automation on site? Because it's not that it doesn't work, it's that it's difficult to integrate with the process today, right? Um, so I think you know, that sort of like holistic motion control for everybody on the job side, right? People and robots, um, to me, that's that's an interesting way to try and bridge the gap instead of thinking about those lower level problems, which somebody has to do, right? But if you can solve the higher level problem to really make them valuable, right? Um, I think that that's one path that that maybe will start to kind of open up some some possibilities.
SPEAKER_00:So what you're saying is we need to embed Neuralink into construction workers and make them part of the construction. I can I've been looking at that actually an application on the phone. No, but it's funny, uh we we had a call with this um hospital system, and they got my name through one of my investors or something, and they said, hey, we're designing this hospital, and our architect hasn't even considered, just not on their radar, the fact that we will have robots and humans coexisting in the facility, right? This isn't you build a building today, it's around for 50 years, right? So we know we can argue about when, I don't think we're gonna argue about if, right? And so when you think about like that, it was fascinating to me. Like, how is an architect not thinking about or an MEP firm, like electrical needs and power needs? It's fascinating that there's oh well we'll we'll get there when we get it. But I think this next phase, you know, we like to your point, right? We may not be at it be a fully automation full automation on a job site, which means there's an interim period where humans and robots are going to coexist. And uh, you know, in a hospital like right now, the the robot just might be delivering your food and taking your dirty trays away. Um now it might be a robot comes and draws your blood.
SPEAKER_02:Yeah, 100%. I mean, um, you know, not that long ago, right? You didn't really, I assume you don't you didn't think about power requirements when you built a parking garage. Right. Right. Now you need to make sure you have quite a bit of current draw, right, to charge your cars. Uh in the same way, you know, you need robot parking at a construction site. You need legitimate power at a construction site, right? To be able to recharge systems at night. Um yeah, I I mean it will be very interesting to see um from commercial buildings to you know construction sites, how people start to think about space, power, um, you know, a variety of different kinds of constraints that are very new. Uh and I would say like not particularly well known, right? Because not all the solutions exist yet. So how do you how do you guess correctly, right? Yeah when you're building these things.
SPEAKER_00:Yeah. Yeah. And I think that's the thing, right? Like, um, what about what did I tell you? I think I said something to you yesterday. It's like um, it's not that it's a bad idea, we just have lots of ideas.
unknown:Right.
SPEAKER_00:It's not that we have no idea, we just have lots of ideas. Yeah, yeah. Yeah. So it's not like there's uh, which is just I I think that's the um it's not a cop-out, right? It's just the reality, right? Like when people ask me, like, what do you think? I'm like, well, I think a lot of things. Let me tell you about the 10 things I'm thinking. You know, it's like which one's the right one? I'm like, I don't know, like TBD, right? TBD.
SPEAKER_01:Yeah.
SPEAKER_00:Um, so what's what's been there been any like big surprises since you joined around like the AEC industry of like um you won't offend anybody because we all know we we know we're kind of quote unquote behind. Is there any like I can't believe they're still doing that that way?
SPEAKER_02:Um I'll start with, you know, you told me that I'll start with something super positive, uh which is maybe more cultural or social, right? But you told me everybody's super friendly and they're gonna be more than happy to talk to me, right? Um, and that's not usually the case in different industries. People usually want to let you know how much they know. Uh, but I've been very impressed by like how open everyone has been, right, to teaching me, like excited. Like if I say something wrong, nobody cares, right? They just tell me what is the right way to say it and go on. So that's what's super positive. So I so you see an industry that I think is excited to change that's willing to change. Um I think, yeah, I think in terms of what has surprised me, you know, so software developers are are notoriously bad at using their project management tools, right? Um, but it seems like in construction they are at least equally an afterthought, right? Um, and it it's not to say, but they like the the tool itself doesn't drive things, right? People drive it, and then you know, those tools are used to keep track of what's done. Yep. Right. Um, they're not used, in my opinion, to really drive what's being done. Right. And so it's it's funny to see kind of that analogous behavior, right? Only in rare instances are you are people who are incredibly well attuned to the tool using it to drive behavior. Typically, it's kind of a record, right? And what's happening, but everything else happens through human interaction discussion. So that was a little surprising because you think of the scale of building something like a hospital, right? You think of the waterfall nature, right? Like when you learn project management, you have um you have lots of different ways of approaching it, right? But you basically have agile and you have waterfall, right? So agile kind of makes more sense to me that that's how it works. Uh waterfall multi-year projects kind of happening in a similar fashion is kind of shocking. Yeah.
SPEAKER_00:Yeah. No, I think that I think that's true. Like everybody's using these systems as archival systems, not as planning systems, you know. And I and I think that is one of the things. It's like, okay, I already did it, let me go put it into the system so that someone knows I did it, versus, hey, here's what I'm gonna go do. Um, and and it and and it's you know, like I think you're right, like in software, like you run a tight shop, but a lot of folks just the planning and uh aspect of kind of PMing stuff is uh I used to joke around, you know, there was a minute there where the tech industry was just hiring a lot of people that weren't really that technical, and which uh kind of in some circles we call them laptop workers because they weren't marketing, they weren't selling, they weren't coding. And the running joke was well, they just update the Trello board, they sit in on stand-ups and update the Trello board for all the coders. And those were the people that you saw hanging out in Starbucks on on Zoom calls laptop workers updated up upload, you know, updating the Trello board, so to speak. Yeah, but uh, I don't think there's a lot of those guys, those folks left. Well, Barry, this was really cool. We'll do this again. Um and uh for those of you listening, if you I'm accessible so many different ways. So I'm not gonna tell you how to find me. Uh I'm easily foundable. Um, but in the future, you know, it'd be great, like if you guys send us topics. I'm sure there's a lot of I know at our Vibathon, you had a lot of people asking you lots of questions about everything. So I feel like uh we're very fortunate uh at our firm to have Barry on board. I think as an industry, we're very fortunate to attract people like Barry. So don't uh if you have questions, definitely send them in and maybe we can aggregate some topics and uh keep doing this. So thanks, Barry.
SPEAKER_02:Yeah, awesome. Thanks, KP. I really enjoyed it. Thanks a lot.